Update readme

README.md

@@ -1,6 +1,7 @@
 # Arabic Dialect Classifier
 This project is a classifier of arabic dialects at a country level:  
 Given some arabic text, the goal is to predict the country of the text's dialect.  
+  
 You can use the "/classify" endpoint through a POST request with a json input of the form: '{"text": "Your arabic text"}'  
 ```
 curl -X POST -H "Content-Type: application/json" -d '{"text": "Your Arabic text"}' http://localhost:8080/classify
@@ -29,4 +30,20 @@ The response should be a json of the form:
 {
     "class": "country_name"
 }
-```
+```
+
+## How I built this project:
+The data used to train the classifier comes from the NADI 2021 dataset for Arabic Dialect Identification [(Abdul-Mageed et al., 2021)](#cite-mageed-2021).  
+It is a corpus of tweets collected using Twitter's API and labeled thanks to the users location with the country and region.  
+
+I used the language model `https://huggingface.co/moussaKam/AraBART` to extract features from the input text by taking the output of its last hidden layer. I used these word embeddings as the input for a Multinomial Logistic Regression to classify the input text into one of the 21 dialects (Countries).
+
+For more detail, please refer to the docs directory.
+
+## References
+- <a name="cite-mageed-2021"></a>
+[Abdul-Mageed et al., 2021](https://arxiv.org/abs/2103.08466)  
+*Title:* NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Task  
+*Authors:* Abdul-Mageed, Muhammad; Zhang, Chiyu; Elmadany, AbdelRahim; Bouamor, Houda; Habash, Nizar  
+*Year:* 2021  
+*Conference/Book Title:* Proceedings of the Sixth Arabic Natural Language Processing Workshop (WANLP 2021)